Find out the time employees spend in the office for a day.

To calculate the time employees spend in the office, you need a log that records each employee’s check‑in and check‑out timestamps. The typical approach is:

1. Load the log into a DataFrame or table.
2. Ensure the timestamps are in a consistent format and cast them to a datetime type.
3. Group the data by employee ID and date.
4. For each group, sort the events chronologically and pair each check‑in with the next check‑out. If the data is clean, you can simply compute the difference between consecutive timestamps.
5. Sum the differences for each employee per day to get the total time spent.
6. Optionally, convert the total seconds to hours/minutes for readability.

Complexity is O(n) where n is the number of log entries. In SQL you could use window functions: LAG() to get the previous timestamp and then subtract. In Spark, use Window.partitionBy("emp_id", "date").orderBy("timestamp") and then compute the difference with lead() or lag().